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genpark-heston-stochastic-volatility-cir-process-skill

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SUMMARY

Heston two-factor stochastic volatility model with Cox-Ingersoll-Ross (CIR) variance and Feller condition checking

README.md

Heston Stochastic Volatility Simulator Skill

Two-factor coupled stochastic differential equation solver featuring CIR variance and correlated Brownian noise.

flowchart TD
    Gaussian["Correlated Gaussians (Z1, Z2 with correlation ρ)"] --> Var["CIR Variance Step: dV = κ(θ - V)dt + ξ √V dW_V"]
    Gaussian --> Price["Price Step: dS = μ S dt + √V S dW_S"]
    Var --> Price
    Var --> Feller["Feller Verification: 2κθ > ξ^2"]

Features

  • 100% Python Standard Library: Full truncation Euler scheme for non-negative variance.
  • Correlated Noise Injection: Cholesky decomposition of 2D Wiener processes.
  • Feller Boundary Check: Automatic analytical positivity verification.

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